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Risk Based Authentication and AM 8. What you need to know!

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#RSAsummit

Agenda

Authentication Manager 8

Customer Use Cases

Risk Based Authentication (RBA)

RBA Integration and Deployment

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SecurID / Authentication Manager 8

AM8 Compelling New Features

Risk-Based Authentication lowers authentication costs

Virtualization better control at lower cost;

Mix & Match between Virtual and/or Physical Appliance

Self Service & Admin Dashboards lowers TCO

Software Token Provisioning improves by 57%

Proven High Quality Release

AM Prime Suite – Advanced Token Lifecycle

Management Solutions

Archer Focused Solutions (Reporting)

Software Token 2.0 Improves User Experience

AM8.0 (Virtual Appliance) GA in

Mar 2013

AM 8.1 (Hardware Appliance)

GA in Dec 2013

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A Few Months Left Until End of Primary Support (EOPS)

The Clock is Ticking

AM 6.1

EOPS Dec 2014

No extensions

Can migrate directly

to 8.x

No Appliance

migration

AM 7.1

EOPS Dec 2014

No extensions

Some Appliances

may migrate

For Migration Resources, visit

www.emc.com/am8

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Risk Based

Authentication

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On-Demand

PC / Web

Browser

Mobile

Embedded

Solutions

Fob / Card

Token

Hybrid

Smart Card

Passwords

Tokenless

Software Tokens

Hardware Tokens

Security & Flexibility

Convenience & Cost

Diverse User Populations Require Choice

Risk-Based Analytics

Employees, Temps, Contractors, Partners, Clients, Customers,

Auditors, Remote Workers

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Manufacturing

Supply Chain Order Management

System hosted by XenApp

Enterprise Web Portal

Web Portals for Employee,

Contractor or Customer Services

RBA Use Case: Web-Based Remote Access

For Employees, Contractors, Partners and Clients

Employees &

Contractors

Partners &

Vendors

Clients

Employee Mobility

SSL VPN and web-based email

for employees & contractors

Healthcare

Health Clinics eliminating the

“token necklace” for medical staff

Professional Services

Exchange of sensitive information

with clients using an online portal

SSL VPN

OWA

SharePoint

Web Portals

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AM8 RBA Customer Implementation

Large Global Media & Marketing Conglomerate with diverse portfolio

of broadcast, digital, mobile and publishing companies

Problem

Solution

Management of digital certificate environment for

authentication is time consuming, tedious and

costly

AM8, 15,000 RBA/ODA Licenses & 15,000 Software

Tokens for multifactor strong authentication, reduced

management & administration costs

Difficulty meeting PCI Compliance

Easily achieves PCI Compliance

Increased risk to the business with potential

outages and breaches

Strengthens access to sensitive applications with

strong authentication for all users (VPN and ODA)

7x24 availability via multiple replicas

VPN access is single factor into corporate network

RBA delivers multi-factor authentication, no impact

to user experience & lowers costs; Software tokens

meet strong 2-factor authentication requirement for

non-Web based applications

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AM8 RBA Customer Implementation

Large North American City Municipality (Population = 1 Million+)

Problem

Solution

Access to HR portal access from internal corporate

network only

Rising help desk costs associated with employees

losing tokens, re-issuing tokens

Cost of issuing tokens to employees who only

require occasional access

Upgrade from AM7.1 to AM 8 Virtual Appliance with

Web Tiers, Self Service Console significantly lowered

deployment, maintenance, Help Desk costs

Deployed 18,000 RBA licenses; RBA licenses do not

expire and can easily be re-provisioned in AM 8

Network utilization, efficiency and negative

experience of dual authentication for an increasing

population of remote users accessing HR portal

indirectly via VPN from home office with a token.

HR portal access from anywhere using RBA has

streamlined operations, lowered cost and improved

user experience.

Tokens moving forward will only be given to users

who have access to critical assets other than their

own HR portal.

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The AM8 RSA Risk Engine

RSA Risk Engine

Based on Adaptive Authentication Risk

Engine

Industry most proven & sophisticated risk engine

Protects 400+ million online identities over last

decade

Optimized for Enterprise Use Cases

Network Security vs. fraud mitigation

Predictable results vs. challenge rate

Assurance levels vs. risk scoring

Simple Deployment vs. customization

Self Tuning Risk Model Adapts to Customer Environment

Common device characteristics de-prioritized in risk score

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Risk-Based Authentication

Strengthens Traditional Password Authentication

By Silently Applying Risk-based Analytics

Web Browser

RSA Risk Engine

Device

Identification

Behavior

User

PASS

FAIL

Protected

Resources

PASS

RISKY

Identity Challenge

?

On-Demand

Challenge

SSL VPN

OWA

SharePoint

Web

Portals

Authentication Policy

Assurance

Level

Activity

Details

Device

Fingerprint

Forensics

Network

Device

Token

Profile

Relative

Velocity

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Risk Assessment

Device Identification

Analyzes Detailed Hardware & Software

Characteristics of Each Device

Behavior Analysis

Assesses Impact of Behavior Anomalies

Based on Frequency and Recentness

Device FingerPrint:

Collects & evaluates multiple

facts about user device such as User Agent String,

System Display, Software Fingerprint, Time Zone,

Languages, Enabled Cookies and Enabled for Java

Profile Anomalies:

Assesses Recent changes to

user profile such as password or account changes

Network Forensics:

Matches device IP

configuration to previously registered IP addresses

for user device; DHCP receives partial credit based

on strength of match

Comparative Anomalies:

Compare behavior

patterns and assesses behavior anomalies such as

new or infrequently used IP address

Device Token:

Identifies device using a combination

of anti-theft protected

Cookies & Flash Shared

Objects (FSO’s)

to prevent impersonation & future

identification & ensure unique match; Without Device

Tokens, strength of match determined by statistical

probability

Velocity Anomalies:

Compares the number of

occurrence within a specified period of time

(velocity) of a user vs. user population

Risk Engine automatically updates scoring algorithm based on statistical

probability of certain characteristics within each unique deployment

Increases

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Assurance Levels

Assurance

Level

Description

Use Case

4 Pre-defined Levels

defined by Policy

Degree of confidence of each

user authentication attempt

Minimum assurance required to authenticate without challenge;

High

BEST for protecting sensitive

assets when higher challenge

rates are acceptable

Authentication from easily-identifiable or corporate-owned

assets (e.g. employee laptop)

Authenticate from same location (e.g. branch or home office)

Medium-High*

VERY GOOD for protecting

sensitive assets when higher

challenge rates not acceptable

Authentication from corporate & individual-owned assets when

policy can be dictated (e.g. cookies must be enabled).

Laptop users that frequently authenticate while traveling

Medium

GOOD when a balance between

protection and end user

convenience is required

Authentication from uncontrolled, non-managed assets (e.g., a

personal laptop or home PC)

When corporate policy cannot be enforced or when tracking

objects (e.g., cookies or FSO) cannot be reliably used

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Device Matching Technique

Device

ID

Match

Behavioral Analysis Risk

Low High

Match based on two or more uniquely

identifying elements & statistical data

Strong

Weak

HIGH

HIGH

MED-HIGH

VERY LOW

Match based on one uniquely

identifying element plus statistical data

MED-HIGH

MEDIUM

LOW

VERY LOW

Match based on one uniquely

identifying element

MEDIUM

MEDIUM

LOW

VERY LOW

Match based on statistical data

VERY LOW

VERY LOW

VERY LOW

VERY LOW

Unrecognized / unbound device

VERY LOW

VERY LOW

VERY LOW

VERY LOW

Assurance Levels Adjusted for Behavioral Risk

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Integration &

Deployment

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End User On-Boarding

Per User by Security Domain

Silent Collection

Self-Service Console

Engine is passive

User login to Self-Service Console

Period of passivity is configurable

(14 Days is Recommended)

User enters step-up challenge based on

policy (Life Questions or On Demand)

User browser session information

collected during authentication

RBA is active immediately

Once assurance reached user

prompted in-line for step up

challenge*

No history

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Risk-Based Authentication Flow

Access Granted

AM Web

Tier

SSL-VPN

S ecu rI D We b A gen t

DMZ

Internet

Lo gin Pa ge (C us to m R BA scr ip t)

Intranet

RBA integration script

redirects to AM web tier

Authenticate user

Create

“auth

artifact”

Return to

SSL VPN

Connect

to

SSL-VPN

AM Appliance

Risk Assessment

(challenge if necessary)

Protected

Resources

Validate artifact

using SecurID APIs

SS C C TKI P R BA

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Certified RBA Integrations

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RSA Authentication

Risk Analytics and Intelligence

AM8 Risk Based

Authentication

Adaptive Authentication

Target Market

Enterprise Web Based Applications

Enterprise / Consumer Portals

Risk Engine

Tuned for Predictable results

Tuned for Predictable challenge rates

Deployment Size Small to Medium - Up to 20,000 users Medium to Large - 10,000+ users

Integration

Plug-and-Play

PS Engagement

Administration

Self-tuning risk engine requires little

administration

Case management allows for manual tuning

by advanced administrators

Policy

Management

Simplified policy management with

pre-defined ‘assurance levels’

Advanced policy management allows

custom weighting of additional risk factors

Devices

Risk engine optimization specific to

SecurID

Risk engine optimizations specific to mobile

devices

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20 © Copyright 2014 EMC Corporation. All rights reserved.

AM8 and Risk Based Authentication

Summary

Optimized for Enterprise Use Cases

Expands the Use of Strong Authentication for Cost Sensitive

Web Applications and Provides User Convenience

Low Cost Alternative for Hardware Authenticators

Simple Plug & Play Deployment

Combo License includes RBA & On-Demand Authentication (ODA)

No Expiration  No Tokens to Purchase or Renew or Re-provision

Self Tuning Risk Model Adapts to Customer Environment

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Common Device Identification Values

Category

Attribute

Description

Token Attributes Cookie Valid browser cookie is present

Flash Valid flash cookie is present

Invalid_cookie Cookie is invalid, expired, or does not match host machine

Invalid_flash Invalid, expired or non-match Flash shared object (FSO) present on host machine No_device_matched Device not previously registered for this user

Network Attributes IP Matches previously known IP address for device

classc Matches previously known Class C subnet for device

classb Matches previously known Class B subnet for device

classa Matches previously known Class A subnet for this device

Device Fingerprint software Software fingerprint based on installed browser plug-ins

usrAgent User Agent String match

browser Browser version match

display Resolution (width/height) & color depth of the device’s display

httpAcceptLang Accept Language String (from the HTTP header)

userLang User Language Preferences

systemLang System Language Settings

browserLang Browser Language Settings

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Common Behavioral Anomaly Events

Category

Anomaly

Description

Profile Anomalies dscPassw The user’s password was recently changed or reset

dscAddr The user’s address was recently updated

dscEmail The user’s email address was recently updated

dscPhone The user’s phone number was recently updated

dscChallengeMethod The user’s challenge method was recently changed dscSecretQuestion The user’s security questions were recently updated

dscProfile Multiple elements of the user’s account were recently changed or updated

dscClearDev The user’s device history was recently cleared

Velocity Anomalies (IP

address) numClassBUsr10d numClassBUsr30d High number of IP (class B) addresses for this user in the last 10 days High number of IP (class B) addresses for this user in the last 30 days

ipAge Length of time since this IP address was first recorded

ipLastHit Length of time since this IP address was last used

ipAuth Recent Identity Confirmation attempts from this IP address were unsuccessful numUsrsIp10m High rate of users authenticating from the same IP address over the last 10 minutes numUsrsIp1h High rate of users authenticating from the same IP address over the last hour numUsrsIp1d High rate of users authenticating from the same IP address over the last day Velocity Anomalies

References

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